Tailored-Made Polydopamine Nanoparticles to Induce Ferroptosis in Breast Cancer Cells in Combination with Chemotherapy

Ferroptosis is gaining followers as mechanism of selective killing cancer cells in a non-apoptotic manner, and novel nanosystems capable of inducing this iron-dependent death are being increasingly developed. Among them, polydopamine nanoparticles (PDA NPs) are arousing interest, since they have great capability of chelating iron. In this work, PDA NPs were loaded with Fe³⁺ at different pH values to assess the importance that the pH may have in determining their therapeutic activity and selectivity. In addition, doxorubicin was also loaded to the nanoparticles to achieve a synergist effect. The in vitro assays that were performed with the BT474 and HS5 cell lines showed that, when Fe³⁺ was adsorbed in PDA NPs at pH values close to which Fe(OH)₃ begins to be formed, these nanoparticles had greater antitumor activity and selectivity despite having chelated a smaller amount of Fe³⁺. Otherwise, it was demonstrated that Fe³⁺ could be released in the late endo/lysosomes thanks to their acidic pH and their Ca²⁺ content, and that when Fe³⁺ was co-transported with doxorubicin, the therapeutic activity of PDA NPs was enhanced. Thus, reported PDA NPs loaded with both Fe³⁺ and doxorubicin may constitute a good approach to target breast tumors.     

Entity linking systems for literature reviews

Scientometrics - Computer-assisted methods and tools can help researchers automate the coding process of literature reviews and accelerate the literature review process. However, existing...     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.

     

Structural,optical and electronic characteristics of Cu and Mg-doped nano MnS sample prepared by molten salt solid state reaction

Journal of Materials Science: Materials in Electronics - Nano Mn0.95M0.05S (M ≡ Cu, Mg) samples were produced using molten salt solid state reaction method. Rietveld analysis of X-ray...     

Influence of the Corrosion Process on Thermotechnical Characteristics of Heat Pipes of Low-Temperature Range

Journal of Engineering Physics and Thermophysics - Results of investigation into the influence of a corrosion process on thermotechnical characteristics of heat pipes of low-temperature range are...     

Magnetically Modified Waste Bark of Aegle marmelos Tree as a Promising Biosorbent for Uranium(VI) Sorption

Radiochemistry - Magnetically modified waste bark of the Aegle marmelos tree was prepared by using green synthesis method and was used in a batch system for U(VI) removal from aqueous solution. The...     

Wall Rock Alteration,Uranium Mineralization,and Potentiality of Uranium and Iron Dissolution from Mineralized Abu Rusheid Gneiss Rock,South Eastern Desert,Egypt

Radiochemistry - Ferrugination, sericitization, desulfitization, chloritization, and kaolinitization of hydrothermal origin are the main wall rock alterations occurring within the NNW shear zones...     

Two-step sinter-crystallization of K2O–CaO–P2O5–SiO2 (45S5-K) bioactive glass

Bioactive glasses and glass-ceramics (GCs) effectively regenerate bone tissue, however most GCs show improved mechanical properties. In this work, we developed and tested a rarely studied bioactive glass composition (24.4K₂O-26.9CaO-46.1SiO₂-2.6P₂O₅ mol%, identified as 45S5-K) with different particle sizes and heating rates to obtain a sintered GC that combines good fracture strength, low elastic modulus, and bioactivity. We analyzed the influence of the sintering processing conditions in the elastic modulus, Vickers microhardness, density, and crystal phase formation in the GC. The best GC shows improved properties compared with its parent glass. This glass achieves a good densification degree with a two-step viscous flow sintering approach and the resulting GC shows as high bioactivity as that of the standard 45S5 Bioglass®. Furthermore, the GC elastic modulus (56 GPa) is relatively low, minimizing stress shielding. Therefore, we unveiled the glass sintering behavior with concurrent crystallization of this complex bioactive glass composition and developed a potential GC for bone regeneration.     

Organizing Production at High-Tech Enterprises in the Digital Era

Russian Engineering Research - The modernization of manufacturing by the comprehensive application of digital technology—in both production and management—is considered. Principles are...